Correlation Analysis of Time and Weight Data

This assignment focuses on a correlation analysis of various time-based variables (time1, time2, time3) and a weight variable (weighttime1). The provided output includes Pearson correlation coefficients, significance levels (p-values), and degrees of freedom for each pair of variables. The analysis aims to determine the strength and statistical significance of relationships between these measures.

SPSS PROJECT

TABLE OF CONTENTS
Chapter 1: Introduction.........................................................................................................................
Background of the study..............................................................................................................1
Rationale of the study..................................................................................................................1
Research Aim and Objectives......................................................................................................1
Chapter 2: Methodology.......................................................................................................................
The Intervention...........................................................................................................................3
Measures......................................................................................................................................3
Participants...................................................................................................................................4
Statistical test...............................................................................................................................4
Chapter 3: Data analysis and results.....................................................................................................
Data analysis................................................................................................................................6
Results..........................................................................................................................................6
Chapter 4: Discussion.........................................................................................................................
Summary of findings.................................................................................................................15
Limitations of study or area future research..............................................................................15
Clinical application....................................................................................................................15
Reference............................................................................................................................................
Appendix............................................................................................................................................

CHAPTER 1: INTRODUCTION
Background of the study
The present report is going to analyze the effectiveness of different treatment procedure
which is applied on distinct individuals for treatment of similar health issues. In this regard, the
present study is going to analyze the effectiveness of different treatments procedures when an
individual is suffering from Leukemia. Considering this, Leukemia is a cancer of the blood cells.
However, there are several broad categories of blood cells which consist of RBCs (Red Blood
cells), WBCs (White Blood Cells) and Platelets. Usually, Leukemia refers to cancers of WBCs.
This severe disease in the human body is treated by a hematologist-oncologist. These are the
doctors who specialize in blood disorders and cancer. There are several therapy of Leukemia
which consist of Chemotherapy, Radiation therapy, Stem cell transplantation, Biological or
immune therapy and Targeted therapy.
In this process, it evaluates the outcomes of a survey that has been carried out among
people who are assessing the treatment for the Leukemia (Kereiakes and Willerson, 2004). In
this process, total population is categorized in two parts in which one group is taking a brand
new therapy for treatment and another group contains of half of total individuals that is
associated with control group and receiving regular care. In order to evaluate the effectiveness of
different treatment procedures of the Leukemia. The present will use SPSS and is going to apply
various tools such as ANOVA and etc. for evaluation of data that has been collected from survey
(Wallnöfer and Hacklin, 2012). In this context, SPSS will be found a great tool for evaluation of
data that has been collected through survey. Application of ANOVA, partial correlation etc.
provides significant assistance for evaluation of several facts associated with the impact of
different treatment procedure through which investigator is able to draw an appropriate
conclusion. The evaluation of data will be carried out as per the certain aims and objectives
Rationale of the study
Herein, study entails about the effectiveness of intervention and control group while
patients getting the treatment of Leukemia. However, with changing environment and people are
becoming more and more educated takes medical services very seriously and they want to know
what doctors are prescribing to them and how they are being treated so that they can easily
evaluate the effectiveness of the services. Along with this, the main purpose of researcher behind
carrying out this study is to enhance the knowledge regarding the disease as well as the
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understanding regarding varied terms like intervention, control group and the Leukemia. Further,
with the help of this study researcher focuses on examining the impact of Leukemia treatment on
the occurrence of relapses.
Research Aim and Objectives
The aim of present study is to evaluate the Effectiveness of Intervention and Control
Group during the Treatment of Leukemia.
Therefore, the sub-aims of present investigation are determined below:
 To summarize the variables involved in the study through application of descriptive
statistics.
 To identify the statistical significance difference between intervention and control tactic
of treatment procedure of Leukemia with the help of Independent T-Test.
 To identify impact of treatment procedure on the occurrence of relapses during the
treatment of Leukemia through application Mann Whitney U Test.
 To identify the effect of diagnosis on self-image index through One Way Annova.
 To assess relations between weight time with different scale of time during treatment
procedures through method of Partial Correlation.
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CHAPTER 2: METHODOLOGY
For assessment of the effectiveness of treatment procedure. This study design was
longitudinal conducted over 6 weeks in which researcher have examined various factors and
elements. In the present investigation, researcher has used quantitative methods.
For the present investigation, participants were randomly selected who are facing
different health issues due to Leukemia. To attain research objectives, participants have been
assigned into two groups; a group is considered as intervention group which is receiving
treatment of Leukemia in the form of a brand new therapy (Jevitt and Smith, 2007). On the other
hand, another group is termed as control group which is receiving traditional treatment of
Leukemia.
In addition to that test scores and quality of life ratings have been collected by researcher
over three time points: pre-intervention, post-intervention and follow up. In this process, half of
total participants have been randomly assigned to receive a brand new therapy/intervention. The
other half is a control group that is receiving regular care from different health care
organizations.
The Intervention
The intervention that was carried out in this study was a brand new therapy for the
treatment of Leukemia. The present research has evaluated the effectiveness of treatment
associated with new therapy in comparison of traditional health care practices.
Measures
In order to generate appropriate outcomes, different kinds of measures were used by
investigator. In this regards, test scores were taken over 3 time points. The Self-image index has
been used at 3 time points that is rated within a possible scale range of 0-15. The scale reflects
the perception of participants about their health issues and diseases during different situation. It
was termed as an important indicator through which effectiveness of different treatment
procedure can be examined for attainment of objectives of research (Jaisankar, 2009). The scores
were measured at baseline pre-intervention, post intervention and follow up. All these activities
were examined the effective of treatment procedure that war managed for the period of 6 weeks.
Number of relapses was considered to examine the discomfort level of participants across
3 time points. Participants from this study needed to tell in depth about their health problems and
issues which have been occurred during treatment producer. Higher number of relapses indicate
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that an individual is facing several health issues due Leukemia. This term has been found very
effective for evaluation of occurrence health issues that hampers effectiveness of health issues.
Diagnosis has been classified under three different categories: pre intervention, during
intervention and post intervention.
Participants
Total number of 45 participants took part in the study that was having mean age of 34.16
and standard deviation was 3.38. (Mean age= 34.16 and SD=3.38). In addition to that 23 out 41
participants were associated with the control group and remaining 23 participants were related to
intervention. There were 24 females (53.3%) and 21 males (46.7%), ages ranging from 27 years
to 43 years. For the present study investigator has considered equal number participants for both
treatment procedures that increased effectiveness of present investigation in the context of
present study.
For carrying out study with an appropriate manner, all the participants are associated with
the stage of 0. As per inclusion criteria, 50% of leukemia patients have been selected to generate
appropriate response about effectiveness of different treatments procedure associated with stage
0 and taking treatment from cancer hospitals based in London. These individual are also able to
understand or read or write English.
By considering exclusion critters, remaining 50% of leukemia patients have been selected
who cannot read or write English. These patients are taking case services from cancer hospitals
which are not based in London.
Variables Variable descriptions Possible range or levels
Age (years) Continuous, interval 23-41
Gender Categorical Male, Female
Group Categorical, independent, between subjects Control, Intervention
Self-image index Continuous, interval 0-15
Time Categorical, independent, within subjects Time 1, 2, 3.
Statistical test
Varied tests have been used in the present study to make in-depth analysis on evaluating
the effectiveness of treatment procedures. Following are the methods employed:
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 Descriptive statistics: Descriptive statistics is the terms given to the analysis of data that
assist in describing, showing or summarizing the information in a meaningful way.
Furthermore, with the help of this tool, mean, standard deviation, range etc. can be
evaluated on the basis of which interpretation can be made.
 Independent T-Test: The main purpose of using Independent T-Test is to evaluate the
statistical different between two or more variables. However, in the present study,
researcher has used this test to evaluate whether there is significance difference between
intervention and control tactic of treatment procedure of Leukemia.
 Mann Whitney U Test: The Mann Whitney U Test is employed to compare different
between two independent variables groups when the dependent variable is either ordinal
or continuous, but not normally distributed. According to the present study, this test has
been use to evaluated the impact of treatment procedure on the occurrence of relapses
during the treatment of Leukemia.
 One way ANOVA: In general, one way ANOVA is the analysis of variance use to
determine whether there are any significant difference between the means of two or more
independent groups. Herein, this tool has been used to evaluate any effect of diagnosis on
self-image index during different treatment situations.
 Partial Correlation: The main purpose behind using partial correlation is to measure the
strength and direction of a linear relationship between two continuous variables whilst
controlling variables for the effect of one or more other continuous variables. In the
present study, researcher used partial correlation to identify whether there is any
relationship between weight times with different scale of time during treatment
procedures of Leukaemia.
In order to examine, perception of people about different treatment procedures, 10 out 45
participants were selected randomly as well as each of them was interviewed about their views
on assessment process by organizing the face to face interviews. In this regard, There were 5
males (50%) and 5 females (50%) and 4 from control groups (40%) and 6 participants were
related to intervention groups (60%) that are taking new therapy. The qualitative approach
provides wide range of information about the personal experience of people who are taking
different treatment in order to resolve health issues. For this section, unstructured interviews
have been taken by researcher through which investigator is able to present good results.
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CHAPTER 3: DATA ANALYSIS AND RESULTS
Data analysis
Quantitative data
The evaluation of quantitative data was being carried out by using SPSS statistical
software. In these process, different tools of SPSS software has been used. First of all,
Descriptive statistics has been used to analyse all the variables involved in the study,
Independent sample t-tests were used significant difference between intervention and control
tactic of treatment procedure of Leukemia.
Mann Whitney U test was applied to examine the impact of treatment procedure on the
occurrence of relapses.
A one way ANOVAs was used to identify the effect of diagnosis on self-image index
during different treatment situations.
Partial correlation was considered by researcher to relations between weight times with
different scale of time during treatment procedures of Leukemia.
Significance of the present study is <0.05
Results
Analysis 1: Descriptive Statistics
According to the Appendix 1:
From the table 1 of Appendix 1, descriptive analysis of all the variables has been
evaluated. However, through the means of this mean, range, standard deviation etc. has been
computed so that analysis can be made. On that basis of mean of gender it can be said that there
are more female respondents that has been selected for the current study. Along with this,
average age of selected respondents is around 34. Further, most of the patients have diagnosed
for the Leukaemia disease. Every variable has constant standard deviation which indicates that
their observation are spread.
Analysis 2: Independent T-test
H0 (Null Hypothesis)-There is not any significance difference between intervention and control
tactic of treatment procedure of Leukemia.
H1 (Alternative Hypothesis) -There is significance difference between intervention and control
tactic of treatment procedure of Leukemia.
As per the Appendix 2
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Time 1- There is significant difference identified between difference between intervention and
control tactic of treatment procedure of Leukemia because (p=0.000 and <0.05). Along with this,
F value in equal variance assumed is 3.357 and the mean difference is 5.52372. Further, through
the help of statistical test std. error difference has been identified in time1 is 1.42127 and
1.43051 respectively.
Time 2- In this stage of treatment procedure, there is similar results identified in comparison of
time 1. The p is 0.002 when equal variance is assumed that determines significant difference
between both treatment procedures. Along with this, F value in equal variance assumed is 6.207
and the mean difference is 4.33597. Further, through the help of statistical test std. error
difference has been identified in time2 is 1.33973 and 1.34984 respectively.
Time 3- At last stage of treatment process, there is significant difference identified between
effectiveness of intervention and control tactic of treatment procedures associated with
Leukemia. This is because the value of p is 0.016 which <0.05. Along with this, F value in equal
variance assumed is 2.820 and the mean difference is 2.98024. Further, through the help of
statistical test std. error difference has been identified in time3 is 1.19382 and 1.20222
respectively.
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Analysis 3: Mann Whitney U test
Is there any impact of treatment procedure on the occurrence of relapses during the
treatment of Leukemia?
As per the Appendix 3
It has found that the mean rank associated with the number of relapses within
intervention group is 25.11. On the other hand, the mean rank of number of relapses within
control group is 20.98.
As per the further evaluation of data shown in appendix 2, it can be concluded that the
occurrence of relapses within control group that are taking tradition treatment is lower than in
occurrence of relapses within intervention group. This is because mean rank of number of
relapses in control group and intervention group is respectively 20.98 (Mean rank of control
group=20.98) and 25.11(Mean rank of intervention group=25.11) (Mann Whitney U=206.5, p=
0.289). Furthermore, mean of number of relapses is 5.8667 and intervention or control .4889.
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While standard deviation for number of relapses and intervention or control is 4.42411
and .50553 respectively.
On the basis of above assessment, it can be stated that treatment procedure is having
significant impact on the emergence of different symptoms and occurrence of relapses during
treatment of Leukemia.
Analysis 4: One Way ANOVA
Is there any effect of diagnosis on self-image index during different treatment situations?
As per Appendix 4
On the basis of descriptive analysis various elements has been evaluated through the
means of which researcher can easily understand the self-image of the Leukemia patients after
each and every diagnosis.
Selfimageindextime1:
However, on the basis of result of descriptive statistics valuable information regarding
mean, mode, standard deviation and 95% confidence level of each self-image index has been
computed. However, the mean clearly indicates that, at the first diagnose the mean of 1.75
indicates that people does not much seriously about the disease of Leukemia. While on the
second diagnose the high value of mean 4.06 clearly indicates that intensely thinks about their
disease. Lastly, in the third diagnose value of mean 3.23 clearly indicates that they thinks about
their disease moderately.
Selfimageindextime2:
On the second time measurement of self-image is based on 0-15 scale in which value of
mean will assist in identifying the actual pressure that patients takes after every diagnosis. In this
regard, at the first diagnose the mean value of 3.75 indicates that patients does not take the high
pressure. While in the second diagnose mean of 6 indicates that there is pressure on the patients
about their Leukemia disease. But on the third diagnose again patients are relax but still get the
high value of mean with 5.00.
Selfimageindextime3:
On the last time, once again the scale of measuring the pressure of patients is every
diagnosis is marked from 0-15. Herein, after 1st diagnose mean value of 4.68 indicates that
patients rate their pressure at low. While at the 2nd diagnose high mean value of 6.6 indicates that
patients have moderate pressure of the Leukemia disease after the treatment. While 3rd and final
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diagnose mean 6.0 clearly indicates that in this stage also Leukemia patients are not in immense
pressure of the treatment they are going through.
Interpretation on the basis of Significance value:
As per table shown in appendix, the significance value for testing the hypothesis is 0.05.
However, if the value of outcome is less than significance value than alternative hypothesis will
be accepted and if it is higher than null hypothesis will be accepted. According to the present
given scenario, the significance value is greater than 0.05 therefore, alternative hypothesis is
rejected and null hypothesis is accepted. Furthermore, at the second diagnose also significance
value is less than of outcome generated, hence, null hypothesis has been accepted (Wild and et
al., 2012). Whereas, in the third diagnose also value of outcome is higher than the significance
value therefore, in all the indexes null hypothesis is accepted which indicates that there is no
statistically significance difference in the mean self-image index on the basis of number of
diagnose. Similar to this, Index 2 and 3 outcomes are also greater than significance value thus, it
can be interpreted that, null hypothesis is accepted and there is no statistically significance
difference in the mean self-image index on the basis of number of diagnose.
Analysis 5: Partial correlation
Are there any relations between weight times with different scale of time during treatment
procedures of Leukemia?
As per Appendix 5
On the basis of above partial correlation, relationship between two or more variable with
the external variable that controls the all the dependent variable is analysed. In the present given
scenario, descriptive statistics of partial correlation indicates that, mean of time 1, 2 and 3 are
showing almost similar results which indicates that there is relationship between all the variables.
Furthermore, through the means of partial correlation, relationship between all three
variables has been identified. However, time 1 is highly correlated with time 2 and 3 as the
results generated (Correlation) are 0.886 and 0.883 respectively. Furthermore, time 2 is also
highly correlated with time 1 and 2 as it the results (Correlation) are 0.886 and 0.916
respectively. Similarly, time 3 is also highly related with the both time 2 and 1 and it shows the
value of .883 and .916 respectively. Lastly, results of weight at all the time of treatments are
relatively low which means, weight times of the patients are not related to the timings of
treatment.
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Ranges and Skewness
On the basis of table shown in Appendix 5, Skewness has been interpreted. The main
purpose behind evaluating Skewness is to measure of symmetry or asymmetry of probability
distribution of real valued random variable about its mean. Furthermore, the value of Skewness
can be either negative, positive or even undefined. For then given data set the measure of
Skewness is having a symmetrical distribution because most of the values are positive.
Number of relapses:
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Intervention control:
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CHAPTER 4: DISCUSSION
Summary of findings
As per the above assessment, there are significant differences identified in effectiveness
of traditional caring practice of Leukemia and new modern therapy. Furthermore, it is examined
that perception of an individual patients of Leukemia about their diseases has significantly
changed in different diagnosis of issues. Furthermore, it is evaluated that patients are identifying
higher relapses while taking treatment through new modern therapy in comparison of traditional
caring practices. As per the above assessment, it has been found that the second diagnose also
significance value is less than of outcome generated with reference to ANOVA. On the other
hand, the value of third diagnose also value of outcome is higher than the significance value that
indicates that there is no statistically significance difference in the mean self-image index on the
basis of number of diagnose. Similar to this, the value of Index 2 and 3 are also greater than
significance value that determines that there is no statistically significance difference in the mean
self-image index on the basis of number of diagnose of Leukemia.
Limitations of study or area future research
The outcomes of present study are limited that due to limited number of participants that has
hampered effectiveness of outcomes of research. Future research should be carried out with
larger sample size and employees from different organisations should participate in the study
(Pallant, 2013). In addition to that further study needs to carry out to examine role of health care
workers in effectiveness of different treatment procedures through which an individual would
assess best services for serious diseases such as cancer and diabetes.
Clinical application
The present study has examined the effectiveness of different treatment tactics used for
treatment of Leukemia. As per the outcomes of present study, management of hospital can use
different treatment tactics such as new modern therapy and traditional caring practices for
handling different health issues which have been faced by an individual due to Leukemia
(Robinson and Castle Bell, 2014). It supports health practitioners in selection of best tool for
caring of mental and physical health in different situations.
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REFERENCE
Books and Journals
Jaisankar, S., 2009. Quantitative Techniques for management. India: Excel books.
Jevitt, S. and Smith, L., 2007. Critical Thinking in Health and Social Care. SAGE.
Kereiakes, D. J., and Willerson, J. T., 2004. US Health Care: Entitlement or Privilege.
Circulation. 109 (12). Pp. 1460–1462.
Pallant, J., 2013. SPSS survival manual. McGraw-Hill International.
Robinson, N. W. and Castle Bell, G., 2014. Rating Slam Dunks to Visualize the Mean, Median,
Mode, Range, and Standard Deviation. Communication Teacher. 28(4). Pp. 218-223.
Theisen, J. L., 2013. Competency of new graduate nurses: a review of their weaknesses and
strategies for success. The Journal of Continuing Education in Nursing. 44(9). pp.406.
Wallnöfer, M., and Hacklin, F. 2012. The business model in the practice of strategic decision
making: insights from a case study. Management Decision. 50(2). pp.166 – 188.
Wild, D. and et al., 2012. Using the ‘Caring for and Caring About’ Model in practice in Care
homes for older people (Part 2). `Nursing Times. 108(12). pp.12-15.
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APPENDIX
Appendix 1:
Descriptive Statistics
N Range Minimum Maximum Mean Std.
Deviation
Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error
gender 45 1.00 .00 1.00 .4667 .50452 .138 .354
age 45 14.00 27.00 41.00 34.1556 3.38416 -.144 .354
selfimageindextime1 45 13.00 .00 13.00 2.9333 3.08516 1.480 .354
selfimageindex2 45 13.00 2.00 15.00 4.8889 2.94049 1.388 .354
selfimageindex3 45 12.00 3.00 15.00 5.7333 2.78307 1.282 .354
interventionorcontrol 45 1.00 .00 1.00 .4889 .50553 .046 .354
weighttime1 45 212.00 98.00 310.00 160.0444 48.06622 1.650 .354
numberofrelapses 45 16.00 .00 16.00 5.8667 4.42411 .765 .354
time1 45 21.00 18.00 39.00 29.2222 5.47676 .110 .354
time2 45 19.00 18.00 37.00 27.5111 4.95260 .150 .354
time3 45 18.00 19.00 37.00 28.0222 4.23454 .288 .354
selfreferred 45 1.00 .00 1.00 .4444 .50252 .231 .354
diagnosis 45 2.00 1.00 3.00 1.9556 .82450 .085 .354
Valid N (listwise) 45
Descriptive Statistics
N Range Minimum Maximum Mean Std.
Deviation
Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statisti
c
Std.
Error
gender 45 1.00 .00 1.00 .4667 .50452 .138 .354
age 45 14.00 27.00 41.00 34.1556 3.38416 -.144 .354
selfimageindextime1 45 13.00 .00 13.00 2.9333 3.08516 1.480 .354
selfimageindex2 45 13.00 2.00 15.00 4.8889 2.94049 1.388 .354
selfimageindex3 45 12.00 3.00 15.00 5.7333 2.78307 1.282 .354
interventionorcontrol 45 1.00 .00 1.00 .4889 .50553 .046 .354
Valid N (listwise) 45
Appendix 2:
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Group Statistics
interventionorcontrol N Mean Std. Deviation Std. Error Mean
time1 intervention 22 32.0455 5.42022 1.15559
control 23 26.5217 4.04373 .84318
time2 intervention 22 29.7273 5.20240 1.10915
control 23 25.3913 3.68953 .76932
time3 intervention 22 29.5455 4.59531 .97972
control 23 26.5652 3.34156 .69676
Independent Samples Test
Levene's Test for
Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
time1
Equal variances
assumed 3.357 .074 3.886 43 .000 5.52372 1.42127 2.65746 8.38998
Equal variances
not assumed 3.861 38.812 .000 5.52372 1.43051 2.62980 8.41763
time2
Equal variances
assumed 6.207 .017 3.236 43 .002 4.33597 1.33973 1.63415 7.03779
Equal variances
not assumed 3.212 37.731 .003 4.33597 1.34984 1.60271 7.06923
time3
Equal variances
assumed 2.820 .100 2.496 43 .016 2.98024 1.19382 .57266 5.38781
Equal variances
not assumed 2.479 38.270 .018 2.98024 1.20222 .54703 5.41344
Appendix 3:
Descriptive Statistics
N Mean Std. Deviation Minimum Maximum
numberofrelapses 45 5.8667 4.42411 .00 16.00
interventionorcontrol 45 .4889 .50553 .00 1.00
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Ranks
interventionorcontrol N Mean Rank Sum of Ranks
numberofrelapses
control 23 20.98 482.50
intervention 22 25.11 552.50
Total 45
Test Statisticsa
numberofrelapses
Mann-Whitney U 206.500
Wilcoxon W 482.500
Z -1.061
Asymp. Sig. (2-tailed) .289
a. Grouping Variable: interventionorcontrol
Appendix 4:
Descriptives
N Mean Std.
Deviation
Std. Error 95%
Confidence
Interval for
Mean
Minimum Maximum
Lower Bound Upper Bound
selfimageindexti
me1
1.00 16 1.7500 2.20605 .55151 .5745 2.9255 .00 6.00
2.00 15 4.0667 3.80726 .98303 1.9583 6.1751 .00 13.00
3.00 13 3.2308 2.83296 .78572 1.5188 4.9427 .00 8.00
Total 44 2.9773 3.10655 .46833 2.0328 3.9217 .00 13.00
selfimageindex2
1.00 16 3.7500 2.20605 .55151 2.5745 4.9255 2.00 8.00
2.00 15 6.0000 3.48466 .89974 4.0703 7.9297 2.00 15.00
3.00 14 5.0000 2.74563 .73380 3.4147 6.5853 2.00 10.00
Total 45 4.8889 2.94049 .43834 4.0055 5.7723 2.00 15.00
selfimageindex3 1.00 16 4.6875 2.08866 .52216 3.5745 5.8005 3.00 8.00
2.00 15 6.6000 3.24698 .83837 4.8019 8.3981 3.00 15.00
3.00 14 6.0000 2.74563 .73380 4.4147 7.5853 3.00 11.00
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Total 45 5.7333 2.78307 .41487 4.8972 6.5695 3.00 15.00
ANOVA
Sum of Squares df Mean Square F Sig.
selfimageindextime1
Between Groups 42.736 2 21.368 2.354 .108
Within Groups 372.241 41 9.079
Total 414.977 43
selfimageindex2
Between Groups 39.444 2 19.722 2.429 .100
Within Groups 341.000 42 8.119
Total 380.444 44
selfimageindex3
Between Groups 29.762 2 14.881 2.009 .147
Within Groups 311.037 42 7.406
Total 340.800 44
Multiple Comparisons
Tukey HSD
Dependent Variable (I) diagnosis (J) diagnosis Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound
selfimageindextime1
1.00 2.00 -2.31667 1.08292 .094 -4.9499 .3166
3.00 -1.48077 1.12509 .394 -4.2166 1.2551
2.00 1.00 2.31667 1.08292 .094 -.3166 4.9499
3.00 .83590 1.14178 .746 -1.9405 3.6123
3.00 1.00 1.48077 1.12509 .394 -1.2551 4.2166
2.00 -.83590 1.14178 .746 -3.6123 1.9405
selfimageindex2
1.00 2.00 -2.25000 1.02407 .083 -4.7380 .2380
3.00 -1.25000 1.04277 .461 -3.7834 1.2834
2.00 1.00 2.25000 1.02407 .083 -.2380 4.7380
3.00 1.00000 1.05887 .616 -1.5725 3.5725
3.00 1.00 1.25000 1.04277 .461 -1.2834 3.7834
2.00 -1.00000 1.05887 .616 -3.5725 1.5725
selfimageindex3
1.00 2.00 -1.91250 .97804 .136 -4.2886 .4636
3.00 -1.31250 .99591 .393 -3.7320 1.1070
2.00 1.00 1.91250 .97804 .136 -.4636 4.2886
3.00 .60000 1.01128 .824 -1.8569 3.0569
3.00 1.00 1.31250 .99591 .393 -1.1070 3.7320
2.00 -.60000 1.01128 .824 -3.0569 1.8569
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Selfimageindextime1
Tukey HSD
diagnosis N Subset for alpha = 0.05
1
1.00 16 1.7500
3.00 13 3.2308
2.00 15 4.0667
Sig. .108
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 14.557.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.
selfimageindex2
Tukey HSD
diagnosis N Subset for alpha = 0.05
1
1.00 16 3.7500
3.00 14 5.0000
2.00 15 6.0000
Sig. .090
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 14.955.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.
selfimageindex3
Tukey HSD
diagnosis N Subset for alpha = 0.05
1
1.00 16 4.6875
3.00 14 6.0000
2.00 15 6.6000
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Sig. .145
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 14.955.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.
Appendix 5:
Descriptive Statistics
Mean Std. Deviation N
time1 29.2222 5.47676 45
time2 27.5111 4.95260 45
time3 28.0222 4.23454 45
weighttime1 160.0444 48.06622 45
Correlations
Control Variables time1 time2 time3 weighttime1
-none-a
time1
Correlation 1.000 .886 .883 .428
Significance (2-tailed) . .000 .000 .003
df 0 43 43 43
time2
Correlation .886 1.000 .916 .273
Significance (2-tailed) .000 . .000 .070
df 43 0 43 43
time3
Correlation .883 .916 1.000 .359
Significance (2-tailed) .000 .000 . .015
df 43 43 0 43
weightti
me1
Correlation .428 .273 .359 1.000
Significance (2-tailed) .003 .070 .015 .
df 43 43 43 0
weighttime1 time1 Correlation 1.000 .884 .864
Significance (2-tailed) . .000 .000
df 0 42 42
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